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Eagelson , P.S, 1991 . Evap. ANNUAL GLOBAL FLUX 577. All Blue figures in thousands of km 3. ATMOSPHERE. Precip . 12.9. 0.001%. 16%. 84%. 23%. 77%. OCEANS. CONTINENTS. 1,338,000. 47,660. Global Runoff 7%. 97%. 2.999%. +7%. -7%. ATMOSPHERE. 484.7. 12.9. 92.3. 444.3. - PowerPoint PPT Presentation
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Eagelson, P.S, 1991.
ATMOSPHERE
OCEANS CONTINENTS
1,338,000
12.9
47,660
97% 2.999%
0.001%
ANNUALGLOBAL
FLUX577
Precip.
Evap.
84%16%
77% 23%
-7% +7%
Global Runoff 7%
All Blue figuresin thousands ofkm3.
ATMOSPHERE
OCEANS CONTINENTS
1,338,000
12.9
47,660
484.7 92.3
444.3 132.7
40.4
WATER BALANCE APPROACH
Input = Output +/- Change in Storage
List List List
Volume of Store = 10 balls
Input = 1 ballper timeperiod
Output = 1ball per time
period
??
Input = Output ………. No change in Storage
WHAT ARE RESIDENCE TIMES?
Average number of samplings required
Volume of Store = 20 balls
Input = 1 ballper timeperiod
Output = 1ball per time
period
??
CHANGE VOLUME OF STORE
Volume of Store = 10 balls
Input = 2 ballsper timeperiod
Output = 2balls per time
period
????
CHANGE RATES OF INPUT AND OUTPUT
Oceans:
STORE
Precipitation
Runoff
Evaporation
Avg. Residence Time = Volume of Store/Average Flux [T] = [L3] / [L3T-1]
2760 yr = 1,338,000,000 (km3)/ 484,680 (km3 yr-1)
Basic time step over which we are completing the accounting.
Avg. Residence Time = Volume of Store/Average Flux [T] = [L3] / [L3T-1]
Volume = 47,659,600 km3
Input rate = Precipitation (23%)Output rate = Evaporation (16%) + Runoff (7%)
Average rate = (23 + (16+7))/2 = 23% of 577,000132,710 km3 per year
Avg. Residence = 47,659,600 / 132,710 = 359 years
Continents:
STORE
Precipitation
Runoff
Evaporation
Atmosphere:
STORE
Precipitation
Evaporation
Precipitation
Evaporation
ContinentsOceans
Avg. Residence Time = Volume of Store/Average Flux [T] = [L3] / [L3T-1]
Volume = 12,900 km3
Input rate = Evap (oceans) (84%) + Evap (continents) (16%)Output rate = Prec. (oceans) (77%) + Prec. (continent) (23%)Average rate = ((84+16) + (77 +23))/2 = 100% of 577,000
577,000 km3 per year
Avg. Residence = 12,900 / 577,000 = 0.02 yrs (7.3 days)
1. Evaporation driven by energy from the Sun, raises water vapor into the atmosphere, renewing the potential energy of the water, and removing most of the dissolved materials inn the water
2. Rising air cools and vapor condenses, releasing energy to atmosphere and forming clouds. Under the correct conditions, the water drops formed will descend under the influence of gravity (kinetic energy) onto the landscape.
3. Water moving over and through the landscape uses both its kinetic energy and propensity to dissolves chemicals, to shape the landscape. Rivers, glaciers, caves, groundwater etc.
4. This kinetic and chemical energy given to the water by the Sun, through the process of evaporation is lost once it reaches sea level or some local “datum”, like a lake.
GLOBAL SIGNIFICANCE OF RESIDENCE TIMES
CHANGING THE TIME SCALE OF THE STUDY
Annual S = 0 (No huge lakes or ice sheets in Florida)
Monthly S ~ Groundwater
Weekly S ~ Lakes, Swamps
Daily S ~ Rivers
Hourly S ~ Soil Moisture
Volume
(km3x103)
Average Residence
Times STORES Oceans Land Snow and ice Groundwater Freshwater lakes Inland Seas Soil moisture Rivers Atmosphere Biosphere
1,338,000.0 24,064.0 23,400.0 91.0 85.0 17.5 2.1 12.9 1.1
~ 4000 years days -10,000 yrs2 weeks-10,000 yrs~ 10 yrs days- year~ 2 weeks ~ 10 days ~ 1 week
The shorter the smaller the time step (hour, day, month, year) over which you are accounting, the more stores need to be considered
Time and Space scales of studies usually related. Small area , short time step, large area, along time step
WHICH STORES CONSIDERED WHEN?
Unless huge lakes or glaciers present
ST. MARY’S RIVER, SW. PIER, MICHIGANIMPACT OF LONG-LASTING STORE
Stow, Lamon, Kratz and Sellinger, 2008. Eos, 89, 41, p. 389-390
Continent
Precipitation (mm)
Evaporation(mm)
Runoff (mm)
Europe
790
507
283
Asia
740
416
324
Africa
740
587
153
North America
756
418
339
South America
1600
910
685
Australasia
791
511
280
Antarctica
165
0
165
Source: Shiklomanov (1990)
WATER BALANCE EQUATIONON A CONTINENTAL SCALE
Input = Output +/- Change in StoragePrecipitation = { Evaporation + Runoff } +/ Change in Storage
Assume ΔS 0 in Long Run
Source: Shiklomanov (1990)
Data provided by Mario Mighty
REGION
Mean AnnualRunoff (mm)
Average Coefficient
Of Variation
World 610 0.43North Africa 200 0.31South Africa 210 0.78Asia 620 0.38N. America 1050 0.35S. America 670 0.35Europe 460 0.29South Pacific 1290 0.25Australia 420 0.70
MEASURES OF GLOBAL VARIABILITY IN FLOW
.
Source: McMahon, T. A., B. L. Finlayson, A. T. Haines, and R. Srikanthan,1992: Global Runoff—Continental Comparisons of AnnualFlows and Peak Discharges. Catena Verlag Paperback, 166 pp
Coefficient of Variation = standard deviation/mean
Big value represents relatively high variability from year to year (inter-annual variability)
REGION
Mean AnnualRunoff (mm)
Average Coefficient
Of Variation
Average ratio of largest annual
flow to the annual mean
World 610 0.43 2.2North Africa 200 0.31 1.8South Africa 210 0.78 3.5Asia 620 0.38 2.0N. America 1050 0.35 2.0S. America 670 0.35 2.1Europe 460 0.29 1.7South Pacific 1290 0.25 1.5Australia 420 0.70 3.1
MEASURES OF GLOBAL VARIABILITY IN FLOW
.
Source: McMahon, T. A., B. L. Finlayson, A. T. Haines, and R. Srikanthan,1992: Global Runoff—Continental Comparisons of AnnualFlows and Peak Discharges. Catena Verlag Paperback, 166 pp
Ratio of the discharge of the biggest flow in a year to the average flow in the entire year.
Big values mean that the biggest flow with in a year (intra-annual) tend to be extremely large in comparison to the other flow
REGION
Mean AnnualRunoff (mm)
Average Coefficient
Of Variation
Average ratio of largest annual
flow to the annual mean
Mean Annual Flood
(m3s-1km-2)
Coefficient of variation of log
of annual floods
World 610 0.43 2.2 0.44 0.28North Africa 200 0.31 1.8 0.05 0.18South Africa 210 0.78 3.5 0.34 0.46Asia 620 0.38 2.0 0.30 0.24N. America 1050 0.35 2.0 0.85 0.25S. America 670 0.35 2.1 0.16 0.14Europe 460 0.29 1.7 0.12 0.17South Pacific 1290 0.25 1.5 1.21 0.22Australia 420 0.70 3.1 0.45 0.45
MEASURES OF GLOBAL VARIABILITY IN FLOW
.
Source: McMahon, T. A., B. L. Finlayson, A. T. Haines, and R. Srikanthan,1992: Global Runoff—Continental Comparisons of AnnualFlows and Peak Discharges. Catena Verlag Paperback, 166 pp
Year0 20 40 60 80 100 120 140 160 180 200
Annual Precipitation
200
400
600
800
1000
1200
1400
0 20 40 60 80 100 120 140 160 180 200
Annual Evaporation (m
m)
0
200
400
600
800
1000
1200
1400
0 20 40 60 80 100 120 140 160 180 200
Annual Hydrologic Flux (m
m)
0
200
400
600
800
1000
1200
1400
PrecipitationEvaporation
P - E = R
P
E
0 20 40 60 80 100 120 140 160 180 200
Annual Runoff (m
m)
0
200
400
600
800
1000
1200
1400
Higher Mean; Higher Variability
Lower Mean; Lower Variability Lower Mean; High Variability
R = P - E
P
E R
Land Use Land Cover
Simulated Year0 50 100 150 200
Sim
ulated Annual F
lux (mm
)
0
200
400
600
800
1000
1200
1400
1600
1800
PrecipitationRunoff
Evergreen ScenarioMean = 800mm; St. Dev. = 150mm; C. of V. = 18.75%ET = 500mmMean = 300mm; St. Dev. = 150mm; C. of V. = 50.00%
POTENTIAL ROLE OF VEGETATION TYPE
C. of. V. = (St. Dev./ Mean)*100Figures based on Australian conditions
Higher ET as trees do not lose leaves
Simulated Year
0 50 100 150 2000
200
400
600
800
1000
1200
1400
1600
1800Deciduous ScenarioMean = 800mm; St. Dev. = 150mm; C. of V. = 18.75%ET = 320 mmMean = 480mm; St. Dev. = 150mm; C. of V. = 31.25%
Sim
ulated Annual Flux (mm
)
Lower ET as trees lose
leaves
JONGLEI CANAL
JONGLEI = DRAINING THE EVERGLADES?
Pielke 2001
BIOTIC PUMP
Condensation
Water as liquid
Water as vapor
Upward motionCooling
Decline in atmosphericPressure as Water Vapor leaves column of gasses
INLAND
Precipitation Declining Exponentially
BIOTIC PUMP
Condensation
Water as liquid
Upward motionCooling
Decline in atmosphericPressure as Water Vapor leaves column of gasses
PressureGradient
BIOTIC PUMP
Condensation
Water as liquid
Water as vapor
Upward motionCooling
Decline in atmosphericPressure as Water Vapor leaves column of gasses